Package index • fmrigds

All functions

MapFamily(): Create a subject-aware map family
MaskPolicy(): Define a mask policy
OTFamily(): Optimal transport family helper
OrthogonalFamily(): Orthogonal map family helper
UncertaintyRule(): Specify how uncertainty is propagated through a map
WarpFamily(): Deformable warp family helper
align(): Align subjects into a consensus space
register_alignment() list_alignments() get_alignment(): Register, list, and get alignments (map families)
apply_common_mask(): Apply a common mask to two realised GDS objects
as_fmri_frame.gds(): Convert a legacy rectangular GDS cube to a canonical frame
as_gds(<NeuroVec>) as_gds(<DenseNeuroVec>): Convert a NeuroVec to GDS
as_gds(<NeuroVol>) as_gds(<DenseNeuroVol>): Convert a NeuroVol to GDS
as_gds(): Coerce common R objects into a GDS
as_gds(<fmri_frame>): Project a rectangular frame to the legacy GDS cube
as_gds(<image_catalog>): Convert image_catalog to GDS plan
as_neurovec(): Convert GDS assay to a 4D NeuroVec
as_neurovol_list(): Convert GDS assay to list of NeuroVol objects
as_plan(): Ensure an object is a plan
assay(): Extract a single assay from a GDS object
assay_info(): Retrieve assay metadata
assays(): Extract assays from a GDS object
assert_compatible_spaces(): Assert compatibility between two spaces
assign_meta(): Assign metadata via regex pattern matching
attach_weight(): Attach a custom weight array to a GDS
coef_array(): Stack coefficient assays into an array
coef_cov_tri(): Retrieve packed covariance triangles for OLS coefficients
col_data(): Extract column (subject) metadata from a GDS object
common_mask(): Compute a common mask between two spaces
compute(): Materialise a plan into a realised GDS
contrast_data(): Extract contrast-level metadata from a GDS object
contrasts(): Extract contrast identifiers from a GDS object
derive(): Record a derivation operation in a plan
detect_adapter(): Detect the best adapter for a source
examination_control(): Configure group examination
examine_group(): Examine subjects under an intended group model
explain() print(<gds>) print(<gds_plan>): Explain objects and plans
explain_plan(): Explain a plan's operations in a tidy table
extract_group(): Extract NeuroVol list for a specific group
find_maps(): Find NIfTI map files with optional subject/contrast hooks
fit_group(): Fit a registered group reducer over frame feature blocks
fmrigds fmrigds-package: fmrigds
new_gds() gds(): Create a Group Data Set (GDS)
gds_from_neurovol_nested(): Create GDS from nested structure of NeuroVol objects
gds_from_neurovols(): Create GDS from lists of NeuroVol objects
gds_from_nifti_maps(): Construct a GDS from NIfTI maps discovered on disk
gds_from_scalar_maps() as_scalar_map_gds(): Create a GDS from subject-level scalar NIfTI maps
gds_metadata(): Construct default metadata for a GDS object
gds_source(): Define a plan source (adapter binding)
gds_to_tibble(): Tidy long-form export for GDS
get_adapter(): Retrieve a registered adapter
get_map_family(): Retrieve a registered map family by name
get_posthoc(): Get post-hoc method by name
get_reducer(): Get reducer by name
group_ols() one_sample() two_sample(): Voxelwise OLS helpers for scalar-map group analyses
group_plan(): Construct a lazy frame-native group-analysis plan
harmonise_contrasts(): Harmonise contrast names in a GDS
image_catalog(): Discover image files and create a catalog
join_meta(): Join external metadata to catalog
list_assays(): List the assays present on a GDS (or that a reducer would produce)
list_map_families(): List registered map families
list_posthoc(): List registered post-hoc methods
list_reducers(): List registered reducers
load_plan(): Load a plan from JSON
make_linear_family(): Convenience helpers to create and register alignments
make_warp_family(): Create a warp-based alignment family from on-disk paths
map_assays(): Map files to assay types
map_linear(): Create a linear map between spaces
map_to(): Add a space transformation to a plan
mask(): Apply a mask policy lazily
metadata(): Extract metadata from a GDS object
model_matrix(): Build a design matrix from attached col_data
new_image_catalog(): Create a new image catalog object
nifti_source(): Construct a NIfTI source specification
plot(<gds_examination>): Plot a group examination
posthoc-methods: Built-in post-hoc correction methods and their output assays
posthoc(): Add a post-hoc operation to a plan
preview(): Preview a small block through the plan
print(<catalog_validation_report>): Print validation report
print(<image_catalog>): Print method for image_catalog
read_catalog(): Read catalog from JSON file
reduce(): Reduce across subjects (meta-analysis)
reducer-lmm: Restricted repeated-measures Gaussian LMM reducers
reducer-ols-voxelwise: Voxelwise OLS reducer (per-sample GLM across subjects)
register_adapter(): Register a storage adapter
register_assay(): Register an assay type
register_map(): Register a map family on a plan or realised GDS
register_nftab_adapter(): Register the neurotabs (NFTab) adapter
register_posthoc(): Register a post-hoc method
register_reducer(): Register a reducer kernel
relabel_subjects(): Relabel subjects in a GDS
result_frame(): Construct a standardized statistical result frame
row_data(): Extract row (sample) metadata from a GDS object
sample_groups(): Extract sample-group metadata from a GDS object
sample_labels(): Extract sample labels from a GDS object
save_plan(): Save a plan to JSON
space(): Extract space descriptor from a GDS object
space_basis(): Create a latent basis space descriptor
space_from_nifti(): Create a voxel space from a NIfTI file
space_parcels(): Create a parcels/ROI space descriptor
space_portability(): Classify the portability of a GDS space
space_sample_labels(): Create a simple label space for tabular samples
space_subset(): Subset a space by sample indices
space_surface(): Create a surface space descriptor
space_voxel(): Create a voxel space descriptor
split(<gds>): Split a GDS object by a grouping variable
subjects(): Extract subject identifiers from a GDS object
subset(<gds_plan>) subset(<gds>) subset(<gds_source>): Lazily subset a plan, source, or realised GDS
subset(<image_catalog>): Subset an image catalog
summary(<gds_examination>): Summarize a group examination
summary(<image_catalog>): Summary method for image_catalog
unique(<image_catalog>): Get unique values of a metadata column
unregister_posthoc(): Unregister a post-hoc method
use_weight(): Convenience helper to use a stored weight array for reduction
validate(): Validate a GDS or plan
validate(<image_catalog>): Validate catalog consistency
with_col_data(): Attach subject-level covariates to a plan or GDS
with_contrast_data(): Attach contrast-level metadata to a plan or GDS
with_row_data(): Attach sample-level metadata to a plan or GDS
write_catalog(): Write catalog to JSON file
write_nifti_assays(): Write image-like GDS assays as NIfTI files
write_out(): Declare an output target for a plan
write_report(): Write a self-contained group-examination report